Download Computational intelligence for missing data imputation, by Tshilidzi Marwala PDF

By Tshilidzi Marwala

Lately, the problem of lacking information imputation has been greatly explored in info engineering.

Computational Intelligence for lacking information Imputation, Estimation, and administration: wisdom Optimization ideas provides equipment and applied sciences in estimation of lacking values given the saw information. supplying a defining physique of study priceless to these all for the sector of research, this publication covers options comparable to radial foundation services, aid vector machines, and crucial part research.

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On the other hand, the steepest descent method is not computationally efficient and, therefore, an improved method needs to be found. In this chapter the scaled conjugate gradient method is implemented (Møller, 1993), which is the subject of the next section. Scaled Conjugate Gradient Method The mechanism by which the free parameters (network weights) are deduced from the data is through using some nonlinear optimization method (Mordecai, 2003), and in this chapter the scaled conjugate gradient method.

Neural networks imputation can be viewed as one example of this class (Nelwamondo, 2008). This technique is also known as Multiple Imputation (MI), and was introduced by Rubin (1987). It merges statistical techniques by producing a maximum-likelihood based covariance matrix and a vector of means. Multiple Imputations involve drawing missing values from the posterior distribution of the missing values, given the observed values and is attained by averaging the posterior distribution for the complete data over the predictive distribution of the missing data.

16 Marwala Doebling, S. , Farrar, C. , Prime, M. , & Shevitz, D. W. (1996). Damage identification and health monitoring of structural and mechanical systems from changes in their vibration characteristics: A literature review (Los Alamos Tech. Rep. LA-13070-MS). New Mexico, USA: Los Alamos National Laboratory. Donders, R. , van der Heijden, G. J. M. , & Moons, K. G. M. (2006). Review: A gentle introduction to imputation of missing values. Journal of Clinical Epidemiology, 59(10), 1087-1091. Ewins, D.

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